The estimation of actual crop evapotranspiration (ETa) maps using complex equations and remotely sensed shortwave and thermal infrared imagery can be challenging and may require input data that are not available. There is an opportunity, therefore to create a simpler and faster method to generate ETa maps using fewer input parameters for situations where limited input data is available or greater uncertainty in the resulting ET estimates are acceptable. We compared the estimates of ETa produced by a crop coefficient and NDVI-based (Kc-NDVI) method to a full energy balance (EB) method. Clear sky images from Landsat 7 and Landsat 8 were processed and used for the ETa estimations from maize during two growing seasons in eastern South Dakota, USA. The results showed that the ETa values from the Kc-NDVI method were lower than the ETa values from the EB method by 18% for 2015 and 11% for 2016 growing season. During study period the accuracy of ETa estimation decreased 17% with the Kc-NDVI method. For both years the mean bias error was 0.81 mm day-1 and the root mean square error (RMSE) was 0.37 mm day-1. The average daily ETa of 5.3 mm day-1. The Kc-NDVI method performed acceptable for ETa estimations, indicating that this method can be used to estimate ETa with minimum input parameters at focused regional and field scales for short time periods.